A Content-Based Image Retrieval System Using Multiple Hierarchical Temporal Memory Classifiers

Xia Zhituo, Ruan Hao, W. Hao
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引用次数: 5

Abstract

This paper presents a content-based image retrieval (CBIR) system using multiple Hierarchical Temporal Memory classifiers. in order to improve the efficiency of image management and retrieval, the CBIR system proposed in this paper take advantage of Hierarchical Temporal Memory Algorithm which replicates the structure and function of the human neocortex. in this study, multiple Hierarchical Temporal Memory classifiers were used to provide an intelligent system that aims to understand a query image's category semantics, rather than the low-level image features for image indexing and retrieval. the system supports query by example image, the experiments based on Internet images show the efficiency of our method.
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基于内容的多层次时间记忆分类器图像检索系统
提出了一种基于内容的图像检索(CBIR)系统,该系统采用多层时间记忆分类器。为了提高图像管理和检索的效率,本文提出的CBIR系统利用了复制人类大脑新皮层结构和功能的分层时间记忆算法。在本研究中,使用多个分层时间记忆分类器来提供一个智能系统,旨在理解查询图像的类别语义,而不是低级图像特征,用于图像索引和检索。系统支持实例图片查询,基于网络图片的实验证明了该方法的有效性。
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